code: def testSVD_HasReasonableAccuracy_TF(self):
      model = _build_model()
      _train_model(model)
  
      model_for_inference = svd.SVD(rank=16).compress_model(model)
  
      _, (x_test, y_test) = _get_dataset()
  
      loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(
          from_logits=True
      )
  
      model_for_inference.compile(
          optimizer="adam", loss=loss_fn, metrics=["accuracy"]
      )
  
      results = model_for_inference.evaluate(x_test, y_test)
  
      self.assertGreater(results[1], 0.60)
  
file_path: model-optimization/tensorflow_model_optimization/python/core/common/keras/compression/algorithms/different_training_and_inference_test.py
imports: import os
  import tempfile
  import tensorflow
  from tensorflow_model_optimization.python.core.common.keras.compression.algorithms import different_training_and_inference
  from tensorflow_model_optimization.python.core.keras.testing import test_utils_mnist
label_desc: Use image node_id 2 for calling the FunctionalTest obj's underlying member method code with example usage: obj.testSVD_HasReasonableAccuracy_TF() without return types